AI Usage-Based Subscription Plans
Project Summary
MyBeautyBubble.com (MBB), a beauty e-commerce platform, aimed to transform its subscription service by integrating AI-driven models. The goal was to create a dynamic, Usage-Based Subscription Plan that catered to customers' individual beauty routines and product usage patterns. By offering a personalized experience with real-time adjustments, the system improved operational efficiency, optimized inventory management, and increased customer retention.
Problem Statement
Before the implementation of the AI-powered model, MBB faced several challenges with its fixed-interval subscription service:
• Inaccurate Forecasting: Customers received products they no longer needed or ran out of essentials due to the system's inability to account for variable beauty routines.
• Rigid Subscription Plans: Customers were forced to cancel and recreate their subscriptions if their needs changed mid-cycle, leading to higher churn.
• Inefficient Inventory Management: Overstocking and understocking frequently occurred because of poor demand forecasting.
• Missed Cross-Selling Opportunities: The platform lacked a personalized recommendation system, missing chances to suggest complementary beauty products.
• Rigid Subscription Plans: Customers were forced to cancel and recreate their subscriptions if their needs changed mid-cycle, leading to higher churn.
• Inefficient Inventory Management: Overstocking and understocking frequently occurred because of poor demand forecasting.
• Missed Cross-Selling Opportunities: The platform lacked a personalized recommendation system, missing chances to suggest complementary beauty products.
Key Objectives
• Personalize Subscription Plans: Tailor subscriptions to each customer’s unique beauty routine and product usage patterns to ensure timely deliveries and reduce cancellations.
• Optimize Inventory Management: Leverage AI to predict product demand and reduce inefficiencies like overstocking and stockouts.
• Increase Revenue through Cross-Selling: Implement AI-driven recommendations to offer personalized product suggestions, such as complementary skincare items.
• Enable Real-Time Modifications: Allow customers to modify their subscriptions dynamically with prorated billing, improving flexibility and user experience.
• Scalability: Ensure the system can grow with the platform as more customers join, maintaining consistent performance and prediction accuracy.
• Optimize Inventory Management: Leverage AI to predict product demand and reduce inefficiencies like overstocking and stockouts.
• Increase Revenue through Cross-Selling: Implement AI-driven recommendations to offer personalized product suggestions, such as complementary skincare items.
• Enable Real-Time Modifications: Allow customers to modify their subscriptions dynamically with prorated billing, improving flexibility and user experience.
• Scalability: Ensure the system can grow with the platform as more customers join, maintaining consistent performance and prediction accuracy.
Solutions Implemented
• AI-Driven Predictive Models to predict customer product needs, personalize recommendations, and enable real-time subscription adjustments
• Customer Dashboard: An intuitive screen that allows customers to track product usage, manage subscriptions, and make modifications with ease
Outcomes Achieved
Within six months of the Pilot Launch:
• 14% increase in subscription revenue due to personalized product recommendations and cross-selling.
• 17% reduction in cancellations as customers were able to modify their subscriptions without hassle
• 12% improvement in inventory efficiency
• 14% increase in subscription revenue due to personalized product recommendations and cross-selling.
• 17% reduction in cancellations as customers were able to modify their subscriptions without hassle
• 12% improvement in inventory efficiency
Responsibilities
(See my Core Responsibilities across all projects)
• Collaborated with the ML specialist to define the key data inputs that would drive the AI models, identifying variables like product type, order frequency, and beauty preferences.
• Ensured the AI models aligned with customer needs, making sure the predictions and recommendations were relevant from a business and beauty perspective.
• Validated model output by testing the results against real-world customer beauty routines to ensure accuracy and relevance.
• Worked with the UX Specialist to design a customer dashboard that provided intuitive access to product usage tracking and subscription modifications.
• Monitored customer experiences during the pilot phase, gathering feedback and iterating with the development team to refine the product and improve the subscription model.
• Ensured the AI models aligned with customer needs, making sure the predictions and recommendations were relevant from a business and beauty perspective.
• Validated model output by testing the results against real-world customer beauty routines to ensure accuracy and relevance.
• Worked with the UX Specialist to design a customer dashboard that provided intuitive access to product usage tracking and subscription modifications.
• Monitored customer experiences during the pilot phase, gathering feedback and iterating with the development team to refine the product and improve the subscription model.
Customer Subscription Screen